Go to:
service menu

Julius Kühn-Institut (JKI)
Federal Research Institute
for Cultivated Plants

Professor Dr. Wilhelm Jelkmann

Address:  Horticulture
Schwabenheimer Straße 101
69221 Dossenheim, Germany

Ms Silvia Kowalczyk-Binder
Tel: +49 (0)3946 47 - 4700
Fax: +49 (0)3946 47 - 4805
E-mail: ow@  julius-kuehn.  de

Address: Viticulture
76833 Siebeldingen, Germany
Tel: 03946 47 4609
ow@  julius-kuehn.  de

branch office at DLR Mosel
Gartenstr. 18
54470 Bernkastel-Kues, Germany
Tel: +49(0)6531 - 956 483

Institute leaflet
Institute booklet

Epidemiology and prognosis

Knowledge of the mode of spread and dispersal of pests and pathogens and the influence of environmental parameters is crucial for the development of disease forecasting systems and the modelling of pest population dynamics.

Abiotic factors like wind-drift, rain-splash and insect vectors are important means of pathogen spread, but agronomic practice including plant protection can also contribute to disease spread. Forecasting systems that assess stage specific and weather dependent infection pressure are important decision support tools for integrated production systems. Characterization of new pest populations and pathogen isolates helps to decipher immigration routes and dispersal pathways.

Data on the biology of the infection process, population dynamics and the plant response to pathogens  and pests are collected in order to develop effective and specific control strategies. The severity and significance of a harmful organism is influenced by climatic conditions and their interaction with plant hosts and other biotic factors. The coincidence of high temperature with humid conditions, for example, is favorable for the quick and severe spread of apple scab. Key parameters for the development of forecasting systems are weather data, host plant phenology and disease inoculum or abundance of pest species. They are included in mathematical models for disease development. Field data provided by weather stations, monitoring traps and the observation of plant and disease development are used for both initializing the models and improving the prognosis.